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Eigenvector centrality

In graph theory, eigenvector centrality (also called eigencentrality) is a measure of the influence of a node in a network. It assigns relative… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
We demonstrate several new aspects of exceptional points of degeneracy (EPD) pertaining to propagation in two uniform coupled… 
2017
2017
This paper is the first chapter of three of the author's undergraduate thesis. We study the random matrix ensemble of covariance… 
2014
2014
: Freebase can be considered as one of the largest sources in the Linked Open Data (LOD) cloud. The paper adopts a graph-driven… 
2014
2014
KOBAN, DONALD DANIEL. Accounting for Uncertainty in Social Network Analysis through Replication. (Under the direction of Dr. Thom… 
2012
2012
The basic idea of the research is to investigate and formalize functional dependency between structural and social measures in… 
2009
2009
Large-scale eigenvalue and singular value computations are usually based on extracting information from a compression of the… 
2009
2009
We present a simplifled model of mechanical behavior of large cantilever arrays with discoupled rows in the dynamic operating… 
2008
2008
One of the fundamental criterion for the successful application of a brain-computer interface (BCI) system is to extract… 
2006
2006
In peer-to-peer (p2p) networks, peer nodes communicate with each other with the help of overlay structure. As the peers in the… 
2004
2004
This year we participated in the Novelty track. To (cid:2)nd the relevant sentences, we combine sentence salience features that…